Receptor-Based Pharmacophore Modeling in the Search for Natural Products for COVID-19 Mpro.

Considering the urgency of the COVID-19 pandemic, we developed a receptor-based pharmacophore model for identifying FDA-approved drugs and hits from natural products. The COVID-19 main protease (Mpro) was selected for the development of the pharmacophore model. The model consisted of a hydrogen bond acceptor, donor, and hydrophobic features. These features demonstrated good corroboration with a previously reported model that was used to validate the present model, showing an RMSD value of 0.32. The virtual screening was carried out using the ZINC database. A set of 208,000 hits was extracted and filtered using the ligand pharmacophore mapping, applying the lead-like properties. Lipinski's filter and the fit value filter were used to minimize hits to the top 2000. Simultaneous docking was carried out for 200 hits for natural drugs belonging to the FDA-approved drug database. The top 28 hits from these experiments, with promising predicted pharmacodynamic and pharmacokinetic properties, are reported here. To optimize these hits as Mpro inhibitors and potential treatment options for COVID-19, bench work investigations are needed.

Computational hunting of natural active compounds as an alternative for Remdesivir to target RNA-dependent polymerase.

The hunt for potential lead/drug molecules from different resources, especially from natural resources, for possible treatment of COVID-19 is ongoing. Several compounds have already been identified, but only a few are good enough to show potential against the virus. Among the identified druggable target proteins of SARS-CoV-2, this study focuses on non-structural RNA-dependent RNA polymerase protein (RdRp), a well-known enzyme for both viral genome replication and viral mRNA synthesis, and is therefore considered to be the primary target. In this study, the virtual screening followed by an in-depth docking study of the Compounds Library found that natural compound Cyclocurcumin and Silybin B have strong interaction with RdRp and much better than the remdesivir with free binding energy and inhibition constant value as êzŒ-6.29 kcal/mol and 58.39 µMêzŒ, and êzŒ-7.93kcal/mol and 45.3 µMêzŒ, respectively. The finding indicated that the selected hits (Cyclocurcumin and Silybin B) could act as non-nucleotide anti-polymerase agents, and can be further optimized as a potential inhibitor of RdRp by benchwork experiments.

Identification of Persuasive Antiviral Natural Compounds for COVID-19 by Targeting Endoribonuclease NSP15: A Structural-Bioinformatics Approach.

SARS-CoV-2 is a positive-stranded RNA virus that bundles its genomic material as messenger-sense RNA in infectious virions and replicates these genomes through RNA intermediates. Several virus-encoded nonstructural proteins play a key role during the viral life cycle. Endoribonuclease NSP15 is vital for the replication and life cycle of the virus, and is thus considered a compelling druggable target. Here, we performed a combination of multiscoring virtual screening and molecular docking of a library of 1624 natural compounds (Nuclei of Bioassays, Ecophysiology and Biosynthesis of Natural Products (NuBBE) database) on the active sites of NSP15 (PDB:6VWW). After sequential high-throughput screening by LibDock and GOLD, docking optimization by CDOCKER, and final scoring by calculating binding energies, top-ranked compounds NuBBE-1970 and NuBBE-242 were further investigated via an indepth molecular-docking and molecular-dynamics simulation of 60 ns, which revealed that the binding of these two compounds with active site residues of NSP15 was sufficiently strong and stable. The findings strongly suggest that further optimization and clinical investigations of these potent compounds may lead to effective SARS-CoV-2 treatment.